Predictive analytics uses data mining, statistics, modeling, machine learning and artificial intelligence to analyze current and historical facts to make predictions about future or otherwise unknown events. This presentation provides an overview of predictive analytics, including its business applications such as customer retention, risk management and operational optimization. Common predictive analytics methods and tools are also discussed.

1. Analytics Overview
An Introduction to Predictive Analytics
Durga Palakurthy
Avance Consulting

2. Agenda
Introduction
What is Analytics and Big data
Over-view of Predictive Analytics
Business applications of Predictive Analytics
Predictive Analytics Tools

3. Introduction
Analytics is understanding of existing data with goal of understanding trends in
comparison
Gain insights Make Decision
Why analytics?
Productivity gains
Process Improvement gains

4. Big Data & 5 V’s of Big Data
Big Data is high volume, high velocity ,high variety information assets that demand
cost effective innovation forms of information processing that enable enhanced
insight, decision making process automation
Volume
Velocity
Variety
Veracity
Value

6. Evolution

7. Data Analysis:

8. What is Predictive Analytics

10. Common Predictive Analytics Methods

11. Common Predictive Analytics Methods

12. Business Applications of Predictive Analytics

13. Predictive Analytics Tools in market

15. Glossary - Some key terms